جست‌وجوی استاد و پژوهشگر

Betsy Sandersمشاهده پروفایل

استاد

• Computer Graphics
• Virtual Environments
• Human-Computer Interaction
• +۳ مورد دیگر

Betsy Sanders is a Professor of Computer Science at Rhodes College, specializing in computer graphics and virtual environments. She has held this position since Fall 2007 and teaches courses ranging from introductory programming to advanced topics in artificial intelligence and operating systems. Her research focuses on improving human interaction within virtual environments, particularly through immersive technologies like head-mounted displays and gesture-based interfaces. She leads a weekly research seminar and has contributed to projects such as the Guru tutoring system, which integrates animated agents into educational software. Dr. Sanders earned a B.S. in Mathematics and Computer Science from Millsaps College, followed by M.S. and Ph.D. degrees in Computer Science from Vanderbilt University. Her work spans desktop and immersive virtual environments, emphasizing spatial cognition, navigation techniques, and user-centered design. She has published extensively on locomotion methods in VR, including studies on walking-in-place interfaces and gesture-based interaction. Education: B.S. Millsaps College, M.S./Ph.D. Vanderbilt University Research Themes: Virtual Environments, Human-Computer Interaction, Educational Technology Lab: Active projects include Guru tutoring system and VR navigation optimization Outside academia, she resides in Midtown Memphis with her family, balancing hobbies like antique shopping and home renovation with her academic commitments.

Xuming Heمشاهده پروفایل

استاد

• Robust Statistics
• Quantile Regression
• Bayesian Inference
• +۷ مورد دیگر

Xuming He is the inaugural Chair of the Department of Statistics & Data Science at Washington University in St. Louis, holding the Kotzubei-Beckmann Distinguished Professorship. Previously, he served as the H.C. Carver Collegiate Professor at the University of Michigan and held roles at the National University of Singapore and the National Science Foundation. His research focuses on robust statistics, quantile regression, Bayesian inference, and interdisciplinary applications in bioinformatics, public health, and atmospheric science. Education: BS in Applied Mathematics (Fudan University, 1984); MS and PhD in Mathematics/Statistics (University of Illinois, 1988-1989). He is a Fellow of the American Statistical Association and the American Association for the Advancement of Science, and currently serves as President of the International Statistical Institute (2023-2025). His work bridges theoretical advancements in statistical methodology with practical applications in clinical trials, environmental science, and sports medicine. Notable contributions include developing scalable quantile regression techniques and promoting reproducible statistical practices through initiatives like the ASA Task Force on Statistical Significance. Awards: Kotzubei-Beckmann Professorship, ISI Presidency, ASA/AAAS Fellowships. His advising and grants focus on advancing statistical methods for complex data structures, with collaborations in concussion research and interdisciplinary data science. He leads the SDS department’s mission to integrate cutting-edge statistical theory with real-world problem-solving.

• Medical Physics
• Radiation Oncology
• Brachytherapy
• +۴ مورد دیگر

Robert Hunter is an Assistant Professor of Interdisciplinary Science at McMaster University, Hamilton, Canada. He teaches core medical-physics courses within the Medical Physics graduate programme and maintains an active research portfolio centred on brachytherapy physics, image-guided radiation therapy, and treatment-plan optimization. Hunter has co-authored 34 peer-reviewed publications since 1997 and participates in multi-centre clinical trials and technology-development projects. Education & Teaching: Instructor, Medical Imaging Systems I (MEDPHYS 770) — 2023-2025 Instructor, Professionalism and Ethics (MEDPHYS 786) — 2024 Instructor, Radioactivity & Radiation Interactions (MEDPHYS 6B03) — 2020 Instructor, Radioactivity & Radiation in Medical Physics (MEDPHYS 4B03) — 2020 Instructor, Radiation Protection & Radiation Biology in Radiation Therapy (MEDRADSC 3U03) — 2018 Research Focus: Professor Hunter’s work integrates experimental medical physics with clinical translation. His main interest is high-dose-rate (HDR) brachytherapy for gynecological, thoracic, and upper-gastrointestinal malignancies. He investigates applicator design, real-time image guidance using 2D/3D registration, MR/CT-based dose verification, and organ-at-risk sparing techniques. Additional scholarly activity includes optical spectroscopy of tissue oxygenation and algorithmic evaluation of segmentation methods. Across 29 mapped publications, 72 % lie in radiation therapy and 14 % in radiology, with the remainder spanning developmental biology and thoracic surgery. Recurrent themes are dosimetric quality assurance, prospective clinical comparisons, and palliative effectiveness of intraluminal brachytherapy. Scientific Awards & Funding: No specific awards or active grants are listed in the McMaster VIVO database at the time of scraping. Collaboration & Supervision: Hunter collaborates with >20 co-investigators, most frequently Drs Ranjan Sur, Joseph Hayward and Thomas Farrell. No formal student advisees are recorded in the supplied text. Laboratory & Teams: While no standalone laboratory title is provided, his teaching assignments and publication network indicate integration with the Medical Physics unit and the Juravinski Cancer Centre at McMaster.

Charles Heplerمشاهده پروفایل

دانشیار

• Computer Science
• Robotics
• Software Engineering
• +۳ مورد دیگر

Charles Hepler is an Associate Professor in the Department of Mathematics & Computing at Mount Royal University since 1997. He teaches computer science courses including introductory programming, robotics, games development, software engineering, and technology and society, alongside general education courses. His most recent publication (2023) focuses on clinical outcomes of physical activity post-epidural steroid injection for lumbar spinal stenosis, published in Archives of Physical Medicine and Rehabilitation . In his spare time, he appears as a character in Randy Schroeder's unpublished work Three for Mirth .

Giuliano Antoniolمشاهده پروفایل

دانشیار

• Software Engineering
• Software Evolution and Maintenance
• Reverse Engineering
• +۵ مورد دیگر

Giuliano Antoniol is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He is a member of the Institute for Data Valorization (IVADO) and has established himself as a prominent researcher in software engineering, with recognition as one of the world's most productive software engineering researchers and among the top 2% most cited researchers in his field. Professor Antoniol's research spans several key areas in software engineering, with a particular focus on software evolution and maintenance, reverse engineering, static code analysis, and empirical software studies. His work frequently addresses practical challenges in software development, including software quality assurance, technical debt identification, and the application of machine learning techniques to software engineering problems. His research group has produced significant contributions to understanding code smells, identifier naming practices, and the impact of programming language features on software quality. His recent publications reveal a strong trend toward the intersection of traditional software engineering with artificial intelligence and machine learning. Many of his 2023-2025 publications focus on the challenges of testing and verifying machine learning systems, analyzing bugs in AI-generated code, and applying search-based techniques to complex software engineering problems. His work demonstrates a consistent empirical approach, with numerous studies analyzing real-world software systems and developer practices. Ranked among the world's most productive software engineering researchers (2021) Among the top 2% most cited researchers in his field (2021) Award for Most Influential Article of the Decade in Software Engineering (2021) Professor Antoniol has supervised an impressive number of graduate students, with 14 completed PhD theses and 18 Master's theses to his credit. His students have explored diverse topics including software testing, technical debt, machine learning applications in software engineering, and code quality analysis. His research has been supported by numerous grants that have enabled extensive empirical studies and the development of innovative software engineering tools and techniques.

Samuel Kadouryمشاهده پروفایل

استاد

• Medical Imaging
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Samuel Kadoury is a Full Professor at the Department of Computer Engineering and Software Engineering at Polytechnique Montréal , where he focuses on Biomedical Technology , Computer Vision , and Medical Imaging . Holding a B.Eng. (Polytechnique) , M.Eng. (McGill) , and Ph.D. (Montreal) , followed by a Postdoc at INRIA , his career bridges Biomedical Engineering and Artificial Intelligence . His research concentrates on Medical Imaging , Machine Learning , and Interventional Navigation Systems , with applications in Neurology , Cardiovascular Interventions , Orthopedics , and Oncology . He develops systems for Image Registration , Segmentation , and Minimally Invasive Treatments , validated through Clinical Trials in adult and pediatric populations. Recent publications highlight his work in GAN-based Image Synthesis , Semi-supervised Learning , and Survival Prediction for cancers. His 223 publications reflect expertise in Medical Image Analysis , AI Applications , and Biomedical Systems . Scientific Awards : 2009 - Prize for best Ph.D. thesis at Polytechnique Montréal He has supervised 5 PhD students and 15 Master's students , including projects on Prostate Cancer Characterization , Spine Surgery Simulation , and Colorectal Liver Metastases . Affiliated with the Institute of Biomedical Engineering and IVADO (Institute for Data Valorization) , his work intersects Modeling , Artificial Intelligence , and Medical Imaging .

• Network Meta-Analysis
• Bayesian Statistics
• Health Technology Assessment
• +۵ مورد دیگر

Kristian Thorlund is a Part-Time Lecturer at McMaster University's Michael G. DeGroote School of Medicine, affiliated with the Department of Health Research Methods, Evidence, and Impact. He specializes in network meta-analysis, Bayesian statistics, and real-world evidence synthesis, with particular focus on clinical trial methodology and health technology assessment. 2016 recognition as one of McMaster's most cited researchers Developed the Highly Efficient Clinical Trials Simulator (HECT) Active contributor to GRADE guidelines and Cochrane systematic reviews His research spans multiple domains including: Advanced statistical methods for indirect treatment comparisons Adaptive clinical trial designs for rare diseases Artificial intelligence applications in evidence synthesis Real-world data integration for regulatory decision-making Thorlund's recent publications (2022-2025) demonstrate methodological innovations in: COPD combination therapy analysis COVID-19 treatment evaluation Personalized oncology outcome measurement AI-driven literature review systems Surrogate endpoint validation Key contributions include: Developing bias quantification frameworks Advancing living network meta-analysis methodology Improving patient data management systems Standardizing master protocol reviews Thorlund collaborates extensively with: Global health organizations Pharmaceutical companies AI development teams International clinical trial networks

Hai Wangمشاهده پروفایل

استاد

• High-Speed Propulsion
• Combustion Chemistry
• Renewable Energy Conversion
• +۵ مورد دیگر

Hai Wang is a Professor of Mechanical Engineering at Stanford University with a distinguished career in combustion science, high-speed propulsion, and renewable energy conversion. His research spans combustion chemistry of conventional and renewable fuels, detonation dynamics, quantum-chemistry guided battery materials design, and transport theories in nanoparticle systems. Education : Ph.D. in Fuel Science from Pennsylvania State University (1992), M.S. in Chemical Engineering from Michigan Technological University (1986), B.Eng. in Polymer Materials from East China University of Science and Technology (1984). He has authored seminal works on soot formation in flames, catalytic oxidation of methane, and laminar flame speed modeling. His recent publications address interdisciplinary challenges such as eco-anxiety and advanced data plane verification. Notable administrative roles include co-founding Hestia Tec, LLC (2010-2014) and serving as President of the Combustion Institute (2024-present). Wang’s work has been recognized with the Humboldt Senior Research Award (2019), Mercator Fellow (2019), and multiple fellowships. He mentors doctoral and master’s students and leads research initiatives like the Combustion Energy Frontier Research Center (2010-2014).

Matthew A Wilsonمشاهده پروفایل

استاد

• Neuroscience
• Cognitive Science
• Memory Processing
• +۳ مورد دیگر

Matthew A. Wilson is the Sherman Fairchild Professor of Neuroscience at the Massachusetts Institute of Technology (MIT), affiliated with the Department of Brain and Cognitive Sciences and the Picower Institute for Learning and Memory. He joined MIT in 1994 after completing his Ph.D. in Computational and Neural Systems at the California Institute of Technology and postdoctoral training at the University of Arizona. His research focuses broadly on understanding neural mechanisms underlying learning, memory, and cognition, with particular emphasis on hippocampal processing, sleep-dependent plasticity, and the development of advanced neurotechnologies. He is the developer of the ONIX platform, an open-source tool for multimodal neural recording and perturbation during naturalistic behaviors. Key Research Areas: Neuroscience, Memory Systems, Neural Networks, Brain Stimulation, Sleep and Learning. Labs: Picower Institute for Learning and Memory and the Wilson Lab at MIT. Dr. Wilson’s work bridges theoretical and experimental neuroscience, with contributions to quantum networks and interdisciplinary healthcare initiatives such as improving palliative care communication in oncology settings. His lab’s innovations in neurotechnology aim to advance understanding of brain dynamics and therapeutic interventions.

Kerby Sheddenمشاهده پروفایل

استاد

• Genomics
• Genetics
• Computational Statistics
• +۳ مورد دیگر

Kerby Shedden is a Professor of Statistics and Associate Chair for Graduate Studies at the Department of Statistics, University of Michigan. He joined the university in 1999 after earning his PhD in Statistics from UCLA. His research focuses on genomics, computational statistics, and statistical software development, with applications in life sciences and collaborative projects such as biomarker screening for cancer and kidney disease outcomes. Shedden teaches courses including Statistics 206 (Introduction to Data Science) and Statistics 600 (Regression Analysis). He actively contributes to educational materials for these courses, emphasizing Python-based data analysis and cloud computing systems like Greatlakes. His GitHub repository hosts open-source tools for statistical analysis, including Python MixedLM and data readers for SAS/Stata files. Shedden's research spans interdisciplinary collaborations, including genetic association studies, cell-based screening, and biomarker development. He maintains an active GitHub presence with contributions to statistical software libraries such as gonpy and Statsmodels-MixedLM. His work bridges methodological advancements in statistics with practical applications in healthcare and environmental science. He holds leadership roles in the department, overseeing graduate programs and PhD administration. His contributions to statistical education and software development highlight his commitment to advancing both academic and applied statistical practices.

Mark van der Laanمشاهده پروفایل

استاد

• Causal Inference
• Targeted Learning
• Computational Biology
• +۷ مورد دیگر

Mark van der Laan is the Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at the University of California, Berkeley, with joint appointments in the Department of Statistics and School of Public Health. He serves as co-Director of the Center for Targeted Machine Learning and Causal Inference (CTML) and Director of the Computational Biology core of the UC Berkeley Superfund Research Program. His research focuses on developing statistical methods for causal and non-causal parameter estimation from complex data structures, particularly through his pioneering work on Targeted Maximum Likelihood Estimation (TMLE) and super learning methodologies. His work bridges advanced statistical theory with practical applications in biomedical research, genomics, and public health. Van der Laan's recent publications demonstrate a strong focus on causal inference methodology applied to real-world medical problems, including long COVID research, nutritional epidemiology, and genomic medicine. His work consistently emphasizes the integration of machine learning with causal inference frameworks to address challenges in high-dimensional data analysis. Scientific Awards: COPSS Presidents' Award (2005) Mortimer Spiegelman Award (2004) van Dantzig Award (2005) As an educator, van der Laan has mentored numerous students through his teaching of advanced courses including PH C240B Biostatistical Methods: Survival Analysis and Causality, PH 243A Multivariate Statistical Methods in Genomics, and PH 296 Causal Inference Seminar. His research group actively develops R packages to translate theoretical methods into practical tools for the research community. He maintains active collaborations with researchers at UC San Francisco, Kaiser Permanente, and the FDA Real World Evidence Group, focusing on applying advanced causal inference methods to solve pressing public health challenges.

Frank den Hartogمشاهده پروفایل

استاد

• Complex Wireless Networked Systems
• Internet of Things (IoT)
• Cyber-Physical Systems
• +۴ مورد دیگر

Frank den Hartog is a Professor at the University of Canberra, holding the Cisco Research Chair in Critical Infrastructure, and an Adjunct Fellow at UNSW Canberra's School of Systems & Computing. His research focuses on complex wireless networked systems, IoT, and Cyber-Physical Systems. Previously, he served as Senior Scientist at TNO (2003–2016) and worked at KPN, pioneering home networking research. He holds a PhD in Physics from Leiden University and an MSc from Eindhoven University of Technology. Dr. den Hartog has led numerous industry-academic projects, including European Horizon 2020 initiatives, and contributed to 73 patents and 67 standardization papers. He actively participates in IEEE and has supervised 7 Master’s/Honours and 2 PhD students. His work has been recognized with academic and industry awards, and he co-authored over 90 peer-reviewed articles. Key affiliations: University of Canberra (Professor), UNSW Canberra (Adjunct Fellow) Education: PhD in Physics (Leiden University), MSc in Engineering (Eindhoven University of Technology) Research Interests: His work spans IoT security, 6G networking, blockchain in IoT, and smart home systems. He emphasizes standardization and interdisciplinary collaboration, addressing challenges in heterogeneous networks and cyber-physical integration. Publications: His recent work explores AI-driven smart home traffic analysis, 6G spectrum sharing, and IoT trust models. These contributions highlight advancements in network security, edge computing, and decentralized systems. Awards: Multiple unspecified academic and industry accolades for innovations in home networking and IoT. Grants/Leadership: Led EU-funded projects, chaired the HGI Technical Working Group (2012–2016), and reviewed journals and conferences. He contributes to the Home Gateway Initiative and collaborates with industry partners, fostering practical applications of theoretical research in telecommunications and cybersecurity.

Saskia Bollmannمشاهده پروفایل

پژوهشگر ارشد

• Functional Magnetic Resonance Imaging (fMRI)
• Ultra-High Field MRI
• Vascular Imaging
• +۳ مورد دیگر

Dr Saskia Bollmann is a Research Fellow at the School of Electrical Engineering and Computer Science, University of Queensland (UQ), within the Faculty of Engineering, Architecture and Information Technology. Her work focuses on advancing functional magnetic resonance imaging (fMRI) techniques, particularly at ultra-high field strengths, and understanding the role of cerebral vasculature in neuroimaging signals. Education: M.Sc. ETH in Biomedical Engineering (Swiss Federal Institute of Technology Zurich, 2013) PhD in Neuroimaging (University of Queensland, 2018) Research Interests: Dr Bollmann’s research integrates engineering and neuroscience to improve fMRI resolution and accuracy. Key areas include: Ultra-high field MRI applications Vascular contributions to fMRI signals Development of imaging tools like VesselBoost for vascular segmentation Neuroimaging data analysis frameworks (e.g., Neurodesk ) Publications: Her work spans 40+ peer-reviewed articles, emphasizing vascular imaging, signal correction, and tool development. Recent studies include fMRI datasets in motor neuron disease and high-resolution vascular mapping at 7T. Grants & Collaboration: Active in interdisciplinary projects, including collaborations with Massachusetts General Hospital and international neuroimaging communities. Her research aligns with open-science principles, promoting reproducibility and accessibility in neuroimaging. Labs & Teams: Leads projects on functional MRI innovation and vascular imaging within UQ’s imaging facilities, contributing to both academic and clinical neuroimaging advancements.

Peter Gilbertمشاهده پروفایل

استاد پژوهشی

• Biomarkers
• Causal Inference
• Clinical Trials
• +۴ مورد دیگر

Peter Gilbert is a Research Professor of Biostatistics at the University of Washington and a member of the Vaccine and Infectious Disease Division at the Fred Hutchinson Cancer Research Center. He specializes in statistical design and analysis of vaccine efficacy trials, particularly for HIV, malaria, and SARS-CoV-2. His research focuses on immune correlates of protection, sieve analysis, and causal inference methods. Dr. Gilbert leads the Statistical Data Management Center for the HIV Vaccine Trials Network (HVTN) and co-directs the Statistical Center for the Coronavirus Prevention Network (CoVPN). Education: B.S. Mathematics, M.S. and Ph.D. in Biostatistics from the University of Washington. Research interests include biomarkers, clinical trial design, survival analysis, and high-dimensional data methods. His work has led to innovations in statistical methods for evaluating vaccine efficacy and understanding pathogen-specific immune responses. Key achievements include developing statistical tools like SieveSifter and contributing to the analysis of the RV144 HIV vaccine trial, which demonstrated partial efficacy. He has advised numerous doctoral students and holds awards such as the Marvin Zelen Leadership Award (2025) and Fellow of the American Statistical Association (2014). Current projects involve analyzing mRNA-1273 vaccine efficacy, SARS-CoV-2 mutations, and dengue vaccine development. His group collaborates extensively with global health initiatives and industry partners to advance vaccine science.

• Neurocritical Care
• Neuroanesthesia
• Critical Care Medicine
• +۳ مورد دیگر

Dr. Christopher Hawthorne is an Honorary Clinical Senior Lecturer at the University of Glasgow's School of Medicine, Dentistry & Nursing, with an affiliation in the School of Psychology & Neuroscience. He is part of the Department of Neuroanaesthesia at the Institute of Neurological Sciences, Queen Elizabeth University Hospital. His research focuses on intracranial pressure monitoring, neurocritical care data analysis, and the application of machine learning in clinical decision-making. Notable contributions include developing protocols for cerebral perfusion pressure optimization and evaluating software adherence to clinical guidelines. Dr. Hawthorne collaborates widely, with key projects such as the CHART-ADAPT initiative aimed at actionable analytics in critical care. He has authored over 20 publications since 2014, addressing topics like telemetric ICP monitoring and public perception of healthcare data use. His work emphasizes translational research, bridging bedside practices with advanced data science techniques.